NAUTICAL RISK INDEX Results Baltic Case study 30 October 2018 - PowerPoint PPT Presentation

NAUTICAL RISK INDEX Results Baltic Case study 30 October 2018 Yvonne Koldenhof (y.koldenhof@marin.nl)

DEVELOPMENT NAUTICAL RISK INDEX Start: SAMSON: Safety Assessment Model for Shipping and Offshore on the North sea (can also be used on other places….)  Important part of safety assessment model is the traffic database/model  SAMSON  route network consisting of waypoint and links with lateral distribution and shipping intensity  First based on experts and traffic databases from e.g. Lloyds  Later – now this database can also be built up using AIS-data Introduction AIS  analysis of the data like density charts, shipping intensities and encounters (near- misses) Combine safety assessment model and AIS-data  Nautical Risk Index 2

NAUTICAL RISK INDEX; DEFINITION Risk index: calculated value for each individual ship indicating the average risk of the ship at that moment. Risk = Probability * Consequences Probability  expected probability of an accident when a ship will be present at the given location (AIS) taking into account different given factors; Consequences  expected consequences given an accident (in this case the expect amount of oil (or chemical) spill); 3

GENERAL IDEA NAUTICAL RISK INDEX (SAMSON) Area layout & Navigational aids & Accident statistics; measures Lloyd’s accident traffic intensity; ( pilot, tug, VTS, etc. ) database 1990 - 2015 Accident frequency models Number of exposures (possible dangerous situations) Number of expected accidents 4 4

RISK INDEX: FREQUENCY MODEL • EXP : Exposure for a certain accident type (i), e.g. encounter • CASRAT : Casualty (accident) rate for a certain accident type (i) for a certain type of ship and ship size P accident ( i ) = EXP( i ) * CASRAT( i, type, size ) • F flag = multiplication factor for flag state (Port State Control List) • F age = multiplication factor for age of the ship • F wind = multiplication factor for wind • F vis = multiplication factor for visibility • F nav = multiplication factor for navigational status P accident ( i ) = F flag * F age * F wind * F vis * F nav * EXP( i ) * CASRAT( i, type, size ) 5

STUDY AREA 6

DENSITY MAPS 7

TRACKS 8

PROCESS BALTIC CASE STUDY: GROUNDING LINES KAART VERVANGEN 9

GRID-SIZE 10x10km 2x2km 5x5km 10

GULF OF FINLAND – SHIP-SHIP COLLISION St. Petersburg Helsinki Tallinn 11

GULF OF FINLAND – SHIP-SHIP COLLISION Ferry / Passenger Tanker 12

GULF OF FINLAND – COMPARISON WITH REAL ACCIDENTS St. Petersburg Helsinki Tallinn 13

GULF OF FINLAND – DRIFTING FREQUENCIES St. Petersburg Helsinki Tallinn 14

SOUTH-WEST PART – SHIP-SHIP COLLISION Gotland Klaipeda Malmo Gdynia Gdansk Rostock 15

SOUTH-WEST AREA – SHIP-SHIP COLLISION Ferry / Tanker Passenger 16

SOUTH-WEST AREA – COMPARISON WITH ACCIDENTS Gotland Klaipeda Malmo Gdynia Gdansk Rostock 17

FOLLOW THE TRACK OF A VESSEL Collision frequency 18

CONCLUSIONS • The Nautical Risk Index can be used in the Baltic Sea area • An approach using AIS and a “real - time” risk calculation can provided insight in the present situation, but also provide insight in certain “hot - spots” and the change of risk in an area over time. • The “model” is still (and will always be) a “living” model/approach, depending on the available data or depending on the purpose, level of detail necessary… 19

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